Wireless Sensor Networks (WSNs) have become widely used in various fields like environmental monitoring, smart agriculture, and health care. However, their extensive usage also introduces significant vulnerabilities to cyber viruses. Addressing this security issue in WSNs is very challenging due to their inherent limitations in energy and bandwidth to implement real-time security measures. To tackle the virus issue, it is crucial to first understand how it spreads in WSNs. In this brief, we propose a novel epidemic spreading model for WSNs, integrating the susceptible-infected-susceptible (SIS) epidemic spreading model and node probabilistic sleep scheduling--a critical mechanism for optimizing energy efficiency. Using the microscopic Markov chain (MMC) method, we derive the spreading equations and epidemic threshold of our model. We conduct numerical simulations to validate the theoretical results and investigate the impact of key factors on epidemic spreading in WSNs. Notably, we discover that the epidemic threshold is directly proportional to the ratio of node sleeping and node activation probabilities.

翻译：无线传感器网络（WSNs）已广泛应用于环境监测、智慧农业和医疗等各个领域。然而，其广泛应用也引入了网络病毒攻击的显著脆弱性。由于WSNs在能量和带宽方面存在固有限制，难以实现实时安全措施，因此解决这一安全问题极具挑战性。要应对病毒问题，首先必须理解其在WSNs中的传播机制。本文提出了一种适用于WSNs的新型流行病传播模型，该模型整合了易感-感染-易感（SIS）流行病传播模型与节点概率性睡眠调度机制——这一优化能效的关键技术。通过微观马尔可夫链方法，推导出该模型的传播方程和流行病阈值。我们进行了数值仿真以验证理论结果，并探究关键因素对WSNs中流行病传播的影响。值得注意的是，我们发现流行病阈值与节点休眠概率和激活概率之比成正比。